README.md

In ribosomeprofiling/ribor: An R Interface for Ribo Files

RiboR

R interface for .ribo files

Ribo Ecosystem

The paper associated with this package and its larger ecosystem can be found here.

Installation

RiboR requires R version 3.6 or higher.

Note For Linux Users

Install dependencies for devtools. For Ubuntu based distributions, you can use the following command.

sudo apt-get install libxml2-dev libcurl4-openssl-dev libssl-dev build-essential m4 autoconf -y

Install Latest Version From GitHub

1) Install devtools

install.packages("devtools")

2) Load the devtools package

library("devtools")

3) Install RiboR from github

install_github("ribosomeprofiling/ribor")

Note for Bioconductor Installation

As it currently stands, this package lives on the devel branch, and it is not on the current release (Bioconductor 3.10). Please use the alternative installation instructions given above.

RiboR will be available via Bioconductor on the next release cycle (Bioconductor 3.11) which is scheduled for the end of April.

Once it is available, the download instructions will be as follows.

Install Latest Version from Bioconductor (Not Yet Available)

if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager")

BiocManager::install("ribor")

Documentation

Here is a walk-through of RiboR.

Citing

RiboFlow, RiboR and RiboPy: an ecosystem for analyzing ribosome profiling data at read length resolution, H. Ozadam, M. Geng, C. Cenik Bioinformatics 36 (9), 2929-2931

@article{ozadam2020riboflow,
  title={RiboFlow, RiboR and RiboPy: an ecosystem for analyzing ribosome profiling data at read length resolution},
  author={Ozadam, Hakan and Geng, Michael and Cenik, Can},
  journal={Bioinformatics},
  volume={36},
  number={9},
  pages={2929--2931},
  year={2020},
  publisher={Oxford University Press}
}

ribosomeprofiling/ribor documentation built on May 21, 2021, 8:02 a.m.